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Peer-Reviewed Academic JournalInternational Journal of Applied Methods in Electronics and Computers
ISSN: 3023-4409DOI Prefix: 10.58190/ijamec
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Pages: 1-4

Design and Acquisition of EOG Based Interactive Communications for ALS Patients

Nese OZKAN •
Ali Işık •
Ugur FIDAN
Publication DateSeptember 24, 2017
Volume / IssueVol. , No. (pp. 1-4)
subject

Abstract

Amyotrophic lateral sclerosis (ALS) is a motor neuron disease caused by loss of function of spinal cord and brain stem nerve cells. Loss of function in nerve cells leads to weakness and explosion (atrophy) in the muscles. The outcome of the weakness in the muscles needs the help of someone. Despite the limitations of the movement, studies on methods of increasing the daily quality of life ALS patients are continuing. Electrooculogram (EOG) signals were taken from an instrumentation amplifier with 48dB gain and 107dB CMMR ratio. A 16Hz Low Pass Filter and a 50Hz Notch Filter were used to increase the signal to noise ratio. EOG signals are digitized with 10bit resolution ADC and applied to ATmega328 microcontroller. So, the software of microcontroller determines the horizontal and vertical movements of the eye. In this way, the interactive PC software was controlled by the EOG signals. EOG-based interactive software which was developed using the C # programming language has provided to patients' daily requirements, social media accounts etc. The system has been tested on healthy subjects and it has been seen that people can control the software by eye movements. As a result, system will be useful not only for ALS patients, but also for permanent or partially bedridden patient (MS, Hemiplegia, etc.)  groups. And also, while the quality of life in the patients' own habitats is being raised, they will also be able to benefit from health services within the scope of home health services.
Keywords:Amyotrophic Lateral Sclerosis (ALS)AtrophyElectrooculogram (EOG)Home Health CareInteractive
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References (13)

Cited Literature
  1. 1

    R. Barea, L. Boquete, M. Mazo, E. López, “System for assisted mobility using eye movements based on electrooculography,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2002, 10(4), 209-218.

  2. 2

    A. R. Kherlopian, J. P. Gerrein, M. Yue, K. E. Kim, J.W. Kim, M. Sukumaran, P. Sajda, “Electrooculogram based system for computer control using a multiple feature classification model,” In Engineering in Medicine and Biology Society, 2006, pp. 1295-1298.

  3. 3

    H. S. Dhillon, R. Singla, N. S. Rekhi, R. Jha, “EOG and EMG based virtual keyboard: A brain-computer interface,” In Computer Science and Information Technology, 2009, pp. 259-262.

  4. 4

    A. Bulling, D. Roggen, G. Tröster, “Wearable EOG goggles: Seamless sensing and context-awareness in everyday environments,” Journal of Ambient Intelligence and Smart Environments, 2009, 1(2), 157-171.

  5. 5

    M. Yan, H. Tamura, K. Tanno, “Development of mouse cursor control system using electrooculogram signals and its applications in revised hasegawa dementia scale task,” In World Automation Congress (WAC), 2012, pp. 1-6.

  6. 6

    A. Ayvaz, G. Ertaş, “Design of an EOG Based Electronic Circuit to Control Actuators,” National Congress of Medical Technology’14, Turkey, 2014, 22-25.

  7. 7

    S. Gürkan, P. A. Öner, A. İstanbullu, S. Doğan, “Designing a Portable Data Acquisition System for Human-Computer Interface Applications,” National Congress of Medical Technology’15, Turkey, 2015, 165-168.

  8. 8

    S. Gürkan, G. Gürkan, A. Kaya, A. B. Uşaklı, “A Novel Eye-Blınk Based Easy Communıcatıon Devıce for Amyotrophıc Lateral Sclerosıs Patıents: Eyepad®,” 2015.

  9. 9

    C. Mondal, M. K. Azam, M. Ahmad, S.K. Hasan, M.R. Islam, “Design and implementation of a prototype electrooculography based data acquisition system,” In Electrical Engineering and Information Communication Technology (ICEEICT), 2015 International Conference on, pp. 1-6.

  10. 10

    H. Tamura, M. Yan, K. Sakurai, K. Tanno, “EOG-sEMG Human Interface for Communication,” Computational Intelligence and Neuroscience, 2016.

  11. 11

    Ministry of Health and its Affiliates Implementing Regulation On The Presentation of Home Health Care Services, 27.02.2015.

  12. 12

    M. Yılmaz, F. Sametoğlu, G. Akmeşe, A. Tak, B. Yağbasan, S. Gökçay, S. Erdem, “In-Home Health Services as an Alternative Form of Presentation of Patient Care,” Istanbul Med Journal, 2010.

  13. 13

    F. Koç and E. Tan, “Amyotrophic Lateral Sclerosis,” TND Neuromuscular Diseases Scientific Working Group.

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How to Cite This Article

N. O., A. I., U. F. (2017). Design and Acquisition of EOG Based Interactive Communications for ALS Patients. International Journal of Applied Methods in Electronics and Computers, 1-4. https://doi.org/10.18100/ijamec.2017SpecialIssue30460